A tie-line power smoothing via a novel dynamic real-time pricing mechanism in MMGs

In a Multi-Microgrid (MMG), the microgrids (MGs) are generally scheduled individually. Uncoordinated operations in the MMG may result in tie-line power congestion, especially in peak-load hours. Previous studies have rarely reported how to coordinate MGs operation by implementing the acquired optimal day-ahead scheduling in a competitive environment. To solve this problem, a new entity- called a microgrid aggregator has been presented to manage trading power between the MMG and the main grid. In this paper, a bi-level optimization model is proposed to control the tie-line power. On the lower level, each MG optimizes its energy trading with the main grid individually and sends the result to the upper level. On the upper level, an aggregator checks the total trading power between the MMG and the grid. In case of any violation, the aggregator activates demand response programs through a represented dynamic real-time pricing. Subsequently, a new rescheduling is implemented by the local controller (LC) in each MG to achieve maximum profit. This process is a cooperative method. Thus, the aggregated profit should be fairly distributed among the microgrids. In this paper, sharing profit between MGs is implemented based on the core concept. The performance of the proposed method is assessed by simulating various scenarios in different seasons and days, which demonstrates the effectiveness and robustness of the proposed method.

Automated summary

This paper proposes a new concept of a microgrid aggregator to coordinate the operation of microgrids in a multi-microgrid system, in order to avoid tie-line power congestion. A bi-level optimization model is used to control the trading power between microgrids, and demand response programs are activated through dynamic real-time pricing for rescheduling to achieve maximum profit.